Twenty-five years ago, a two-year old with liver failure had no medical or surgical options for survival. Now, with rapid advances in hepatology, surgical techniques, and pharmacology, the same two-year old can receive a liver transplant and, with ongoing treatment, a potentially normal life expectancy. Some 500 children undergo pediatric liver transplantation (PLT) annually in the U.S. alone, and in 2006 there were 5,500 patients in the US still living who had benefitted from a transplant procedure provided by the nation's PLT community of healthcare providers. The PLT community is at the leading edge of pursuing state-of-the-art care in chronic diseases. They are the authors of treatment innovation and measuring resulting outcomes. The PLT community is composed of a handful of regional clinical research medical centers, spread across North America;these centers together have driven significant improvements of care for these sick kids. The PLT community must keep pace with rapidly evolving advances in protocols, pharmacology and surgical techniques, and is constantly exploring better ways to achieve better patient outcomes. But which care processes and treatments are best? The traditional tools for assessing treatment and outcomes cannot keep pace with the rapid change in PLT2 e.g., a multi-center clinical trial often takes as much as ten years to conceive, fund, execute, assess, and publish. IoSemantics, a proven innovator in Semantic Technologies, has assembled a national-caliber interdisciplinary RandD team from the fields of academic medicine and informatics that is ideally suited to applying Semantic Technologies and Social Computing to our proposed clinical outcomes-based informatics solution: Clinical Model- Centered Collaboration (CMCC). CMCC adapts the Open Source software philosophy to medical informatics by: 1) Permitting every PLT center to author and maintain its own disease map and protocols, and map patient status and outcomes to their own clinical model and terminology;and 2) Allowing any PLT center to view and analyze the whole community's variation and experience in a comprehensive fashion, as if it were a centralized database. This unique, next-generation combination of distributed empowerment to individual PLT centers and centralized analysis on the PLT community level has the potential to accelerate the assessment of PLT clinical outcomes and to match the pace of the community's clinical advances in what is essentially a "real time" delivery system. The ioSemantics RandD team proposes an ambitious Phase I project designed to prove the feasibility of integrating and "surfacing" the informatics of clinical variability in the relatively small pediatric liver-transplant (PLT) community to demonstrate the value of the novel CMCC approach described above. We propose to do so via an innovative blend of social computing, collective intelligence, and semantic web with the goal of providing an initial indication using a pre-prototype version that such a system can significantly benefit patient outcomes. Phase I success will set the stage for a larger Phase II prototype/demonstration project. PUBLIC HEALTH RELEVANCE: The 500 children per year who benefit from pediatric liver transplants (PLTs) provided by the approximately 40 North American PLT centers represent just one of the many groups of patients with chronic diseases who receive highly specialized and complex care-the goals of which are achieving normal life expectancy and high quality of life. To realize these goals, best-practices treatment of these patients is rapidly evolving independently at individual PLT centers, but the traditional methods of sharing and validating practices in the academic medicine community- such as long-term clinical trials and refereed journal publications-cannot keep up with the pace and diversity of treatments and outcomes. IoSemantics'unique RandD team of PLT practitioners and computer/informatics experts proposes a multi-phase SBIR project designed to augment traditional approaches by developing and validating a system that combines Semantic Technologies and Social Computing to produce a novel clinical outcomes-based informatics solution: the Clinical Model-Centered Collaboration (CMCC).